Observer-based Consensus for Second-order Nonlinear Multi-agent Systems via Adaptive Repetitive Learning Control

被引：0
|
作者：
Niu, Yanru [1 ]
机构：
[1] Univ Xidian, Inst Machemat & Stat, Xian 710126, Shanxi, Peoples R China
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (IEEE ICIA 2017) | 2017年
关键词：
Multi-agent systems; observer-based; consensus protocols; adaptive repetitive learning control; Lyapunov stability theory; FINITE-TIME CONSENSUS; TRACKING CONTROL; DESIGN; COORDINATION; ROBUSTNESS; TOPOLOGIES; NETWORKS; LEADER;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, we consider the consensus tracking for second-order multi-agent systems via adaptive repetitive learning control. Under the assumption that the velocity information may be unmeasured for any of the following agents, an observer-based distributed adaptive repetitive learning consensus protocol is designed. Based-on the Lyapunov stability theory, a sufficient condition which guarantees the following agents tracking the leader uniformly in the finite time interval is derived. Finally, simulation results are given to illustrate the performance and effectiveness of our proposed protocols in this article.
引用
收藏
页码：632 / 637
页数：6
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